The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Firm-Created Word-of-Mouth Communication: Evidence from a Field Test
Abstract
In this paper, we investigate the effectiveness of a firm's proactive management of customer-to-customer communication. We are particularly interested in understanding how, if at all, the firm should go about effecting meaningful word-of-mouth (WOM) communications. To tackle this problem, we collect data from two sources: (1) we implement a large-scale field test in which a national firm created word of mouth through two populations: customers and noncustomers, and (2) we collect data from an online experiment. We break our theoretical problem into two subproblems. First, we ask: “What kind of WOM drives sales?” Motivated by previous research, we hypothesize that for a product with a low initial awareness level, WOM that is most effective at driving sales is created by less loyal (not highly loyal) customers and occurs between acquaintances (not friends). We find support for this in the field test as well as in an experimental setting. Hence, we demonstrate the potential usefulness of exogenously created WOM: conversations are created where none would naturally have occured otherwise. Then, we ask: “Which agents are most effective at creating this kind of WOM?” In particular, we are interested in evaluating the effectiveness of the commonly used opinion leader designation. We find that although opinion leadership is useful in identifying potentially effective spreaders of WOM among very loyal customers, it is less useful for the sample of less loyal customers.
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Oh, C., & Sheng, O. R. L. (2011) · Journal of the Association for Information Systems · Cited by 182
Hornik, J., Satchi, R. S., Cesareo, L., & Pastore, A. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.11.008 · Cited by 174
“The two procedures were drawn from previously validated procedures and measures (Chen et al., 2011; Godes & Mayzlin, 2009).”
BackgroundMethodNegative Reviews, Positive Impact: Consumer Empathetic Responding to Unfair Word of Mouth
Allard, T., Dunn, L., & White, K. (2020) · Journal of Marketing · doi:10.1177/0022242920924389 · Cited by 177
Aral, S., & Walker, D. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.1564856 · Cited by 173
To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns
Minnema, A., Bijmolt, T. H. A., Gensler, S., & Wiesel, T. (2016) · Journal of Retailing · doi:10.1016/j.jretai.2016.03.001 · Cited by 169
Selectively Emotional: How Smartphone Use Changes User-Generated Content
Melumad, S., Inman, J. J., & Pham, M. T. (2019) · Journal of Marketing Research · doi:10.1177/0022243718815429 · Cited by 182
“Prior work on online WOM has shown that its impact or persuasiveness depends on factors such as the characteristics of the reviewer (e.g., Godes and Mayzlin 2009) and the characteristics of the review itself, such as its linguistic characteristics (e.g., Schellekens, Verlegh, and Smidts 2010).”
Receiver responses to rewarded referrals: the motive inferences framework
Verlegh, P. W. J., Ryu, G., Tuk, M. A., & Feick, L. (2013) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-013-0327-8 · Cited by 161
“However, Godes and Mayzlin (2008) showed that WOM programs may trigger referrals from customers who would otherwise would not be reached otherwise, and they may be effective if they are not perceived as blatant persuasion attempts.”
BackgroundZhang, W., Chintagunta, P., & Kalwani, M. U. (2021) · Journal of Marketing · doi:10.1177/0022242920985784 · Cited by 129
“In the context of online social media, the literature has examined the roles of influencers in consumer marketing (e.g., Goldenberg et al. 2009; Gong et al. 2017; Katona, Zubcsek, and Sarvary 2011) and opinion leaders in business marketing (Hada, Grewal, and Lilien 2014; Iyengar, Van den Bulte, and…”
BackgroundMotivations to interact with brands on Facebook – Towards a typology of consumer–brand interactions
Azar, S., Machado, J. C., de Carvalho, L. V., & Mendes, A. (2016) · Journal of Brand Management · doi:10.1057/bm.2016.3 · Cited by 157
Modeling the role of message content and influencers in social media rebroadcasting
Zhang, Y., Moe, W. W., & Schweidel, D. A. (2016) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2016.07.003 · Cited by 173
“Along with Goldenberg et al (2009), they characterize individuals who follow a large number of others as information seekers while those who are followed by others are characterized as information disseminators.”
BackgroundBlogs, Advertising, and Local-Market Movie Box Office Performance
Gopinath, S., Chintagunta, P. K., & Venkataraman, S. (2013) · Management Science · doi:10.1287/mnsc.2013.1732 · Cited by 153
“Finally, in a recent paper, Godes and Mayzlin (2009) explore the effects of firmgenerated WOM communication.”
Grewal, L., Stephen, A. T., & Coleman, N. V. (2019) · Journal of Marketing Research · doi:10.1177/0022243718821960 · Cited by 151
“We consider situations in which consumers have been prompted to post, as this imitates real social media practice wherein brands encourage posting and engagement from consumers (Chae et al. 2017; Godes and Mayzlin 2009).”
BackgroundThe Economics of Buyer Uncertainty: Advance Selling vs. Probabilistic Selling
Fay, S., & Xie, J. (2009) · Marketing Science · doi:10.1287/mksc.1100.0576 · Cited by 146
Song, T., Huang, J., Tan, Y., & Yu, Y. (2019) · Information Systems Research · doi:10.1287/isre.2018.0797 · Cited by 148
Engineering social contagions: Optimal network seeding in the presence of homophily
Aral, S., Muchnik, L., & Sundararajan, A. (2013) · Network Science · doi:10.1017/nws.2013.6 · Cited by 149
“Specifically, a firm may encourage current adopters to exert more influence on their peers (Godes & Mayzlin, 2009) or alternatively may increase the susceptibility of potential customers to the influence of their peers (Aral & Taylor, 2011); some firms may choose to do both.”
BackgroundSocial Contagion in New Product Trial and Repeat
Iyengar, R., den Bulte, C. V., & Lee, J. (2015) · Marketing Science · doi:10.1287/mksc.2014.0888 · Cited by 147
“…but, to our knowledge, only in the realm of new product adoption (e.g., Aral and Walker 2012, Goldenberg et al. 2009, Hu and Van den Bulte 2014, Iyengar et al. 2011a, Katona et al. 2011) or outside the realm of new products altogether (e.g., Godes and Mayzlin 2009, Trusov et al. 2010).”
BackgroundHsu, L., & Lawrence, B. (2015) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2015.04.004 · Cited by 157
“(Godes and Mayzlin 2009).”
BackgroundTweeting as a Marketing Tool: A Field Experiment in the TV Industry
Gong, S., Zhang, J., Ping, Z., & Jiang, X. (2017) · Journal of Marketing Research · doi:10.1509/jmr.14.0348 · Cited by 146
Seeing Ourselves in Others: Reviewer Ambiguity, Egocentric Anchoring, and Persuasion
Reczek, R. W., Lamberton, C. P., & Norton, D. A. (2011) · Journal of Marketing Research · doi:10.1509/jmkr.48.3.617 · Cited by 145
“Practical Implications Marketers are increasingly interested in proactively managing customer-to-customer communication (Godes and Mayzlin 2009).”
BackgroundFu, P.-W., Wu, C., & Cho, Y.-J. (2016) · Computers in Human Behavior · doi:10.1016/j.chb.2016.10.010 · Cited by 162
“The marketing literature has documented thatWoM, especially from significant others, has a decisive influence on consumers' purchasing decisions (Chevalier & Mayzlin, 2006; Godes & Mayzlin, 2009).”
BackgroundDynamic Effectiveness of Advertising and Word of Mouth in Sequential Distribution of New Products
Bruce, N. I., Foutz, N. Z., & Kolsarici, C. (2012) · Journal of Marketing Research · doi:10.1509/jmr.07.0441 · Cited by 147
“…multiple distribution stages, and their relationship with other aspects of consumer behavior, such as observational learning, or firm decisions, such as participation in stimulating WOM (Godes and Mayzlin 2009) or whether to provide review platforms (Chen, Wang, and Xie 2011; Chen and Xie 2008).”
BackgroundDou, Y., Niculescu, M. F., & Wu, D. J. (2012) · Information Systems Research · doi:10.1287/isre.1120.0463 · Cited by 139
“Godes and Mayzlin (2009) empirically study how firms should strategically recruit customers for WOM campaigns based on loyalty considerations to drive sales.”
BackgroundeWOM credibility on social networking sites: A framework
Moran, G., & Muzellec, L. (2014) · Journal of Marketing Communications · doi:10.1080/13527266.2014.969756 · Cited by 179
Measuring Information Diffusion in an Online Community
Garg, R., Smith, M. D., & Telang, R. (2011) · Journal of Management Information Systems · doi:10.2753/mis0742-1222280202 · Cited by 137
“! ! #! significant impact on online community members, empirical research is only beginning to analyze how online social communities help users discover and diffuse new content [2, 23, 24, 42].”
BackgroundIT-Enabled Broadcasting in Social Media: An Empirical Study of Artists’ Activities and Music Sales
Chen, H., De, P., & Hu, Y. J. (2015) · Information Systems Research · doi:10.1287/isre.2015.0582 · Cited by 137
Herding and Social Media Word-of-Mouth: Evidence from Groupon1
Li, X., & Wu, L. (2013) · MIS Quarterly · doi:10.25300/misq/2018/14108 · Cited by 155
Metadata
- Authors
- Godes, D., & Mayzlin, D.
- Affiliations
- Harvard University (US)
- Yale University (US)
- Venue
- Marketing Science
- Published
- 2009-07
- Volume
- 28
- Issue
- 4
- Pages
- 721-739
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W2132559268
- Cited by
- 837
- References
- 59
- Citations by year
- 2026: 11 · 2025: 22 · 2024: 24 · 2023: 52 · 2022: 41 · 2021: 46 · 2020: 54 · 2019: 55 · 2018: 52 · 2017: 50 · 2016: 57 · 2015: 72 · 2014: 73 · 2013: 81 · 2012: 53
- FWCI
- 155.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Marketing Science (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- word of mouth, opinion leadership, customer loyalty, sales effectiveness, customer awareness
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